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Proceedings Paper

The application of transfer learning for scene recognition
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Paper Abstract

Video is often accompanied by advertisement recommendation, which is an important part of it. In order to make the recommendation of advertisements intelligent, it is important to know the categories of scenes in videos. Although scene recognition and classification have been extensively studied, most methods require a large amount of data sets and training time. To address this issue, we adopt transfer learning t, which has achieved great success in visual tasks with high accuracy and small data set. In this scheme, we propose a model which can be applied to intelligent recommendation of advertisements. We chose class places from taskonomy as our source task model, and it has relatively good accuracy after freezing and training. Our model is not only suitable for indoor scenes, but also suitable for several outdoor scenes which often appear in video and have advertising value.

Paper Details

Date Published: 27 November 2019
PDF: 6 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132107 (27 November 2019); doi: 10.1117/12.2538683
Show Author Affiliations
Boyi Hong, Communication Univ. of China (China)
Cong Jin, Communication Univ. of China (China)
Nansu Wang, Communication Univ. of China (China)
Yajie Li, Communication Univ. of China (China)
Hongliang Wang, Communication Univ. of China (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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